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Hi! I'm Ian Witten from the beautiful University
of Waikato here in New Zealand, and I want
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to tell you about our new online course: Advanced
Data Mining with Weka.
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If you liked the other courses--Data Mining
with Weka and More Data Mining with Weka--you'll
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love this new course.
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It's the same format, the same software, the
same learning by doing, and the aim is the
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same, too: to show you how to use powerful
techniques of data mining on your own data.
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One difference is that the lessons in this course
are given by different people.
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In fact, you'll get to meet pretty well the
whole Weka team in this course.
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This new course is advanced.
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We're going to be looking at new kinds of
data.
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We're going to be looking at time series,
for example, where the data evolves over time
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and your job is to predict the future.
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Or situations where the characteristic of
the source changes slowly over time,
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like it does in real life, and your job is
to track those changes.
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We'll look at different ways of working with
big data.
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We're going to introduce you to Weka's big
sister, Moa, which is a stream-oriented data
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mining system that never stores the data in
main memory, so it can operate on effectively
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infinite streams of data and has to use special
algorithms to deal with these streams,
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which we'll explain to you.
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We'll also show you how to deploy Weka on
a cluster computing environment using the Apache
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Spark framework, and also the popular Hadoop
framework.
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We're going to show you how you can reach
out to other data mining systems from Weka,
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for example, the popular R data mining system.
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You can get at all the algorithms in R,
all the mining algorithms and all the
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very powerful information display capabilities
right there within your Weka interface.
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We'll look at scripting Weka in Python, and
you can write little Python scripts right
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there in the Weka interface.
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We'll show you how to set up the Python Weka
wrapper, where you can access the Weka API
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right from within your very own Python program.
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By popular demand, we've included some applications.
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We'll talk about the application of Weka to
soil sample analysis, where machine learning
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can effectively replace time consuming wet
chemistry.
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We'll look at signals from your brain, functional
MRI signals, which treats the brain as a set
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of voxels that extends over time, a kind
of four-dimensional dataset of what's happening
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in your brain and how to analyze this kind
of data.
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We'll look at a bioinformatics application:
signal peptide prediction.
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We'll look at some image processing stuff,
some filters for getting features off images;
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and we'll look at a Twitter application where
you use Weka to do text mining on a Twitter
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feed.
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This course is aimed at teaching you the principles
and practice of data mining.
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We don't look at the technical details of
particular algorithms.
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In fact, you don't need any special mathematical
background to do this course.
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Indeed, you don't need any programming background.
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We'll see some little Python programs, but
you can pick that up along the way.
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We'll show you how, don't worry.
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Other things for this course ... You're going
to need a computer, of course.
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You're going to need an internet connection.
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You're going to need a Google account, because
again we're using the Google infrastructure
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to deliver the course.
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You will need a few hours a week each week.
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You'll need a lot of motivation.
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This is difficult stuff.
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You're going to learn a lot.
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The course lasts five weeks.
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There are six lessons each week, and each
lesson comprises a short video like this one,
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followed by an activity where you get to practice
what you've learned on a dataset that we provide.
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And there are a couple of tests:
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if you do well enough in those, you'll receive
a statement of completion from the University
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of Waikato, signed by me.
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What else? Textbook? There is no textbook.
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This stuff isn't in the books.
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And I've recorded a new piece of music for you,
some improvisations on a jazz theme by Dizzy Gillespie.
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And the price of admission is zero.
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This course is absolutely free.
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So that's it.
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Advanced Data Mining with Weka, coming soon
to a computer near you.
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Hope to see you there.
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Bye for now!